Skill UI

An advanced debugging skill designed for AI agents. It utilizes gdb-cli to provide intelligent assistance for C/C++ programs, enabling the analysis of core dumps, debugging live processes, and investigating complex issues like crashes, deadlocks, and memory corruption. It correlates runtime state inspection with source code context for deeper insights.

Register ICANN domains via a REST API with crypto payments so AI agents can autonomously check availability, pay in USDC/USDT/ETH/BTC, and retrieve DNS management credentials.

AegisOps-AI is a professional-grade 'Living Pipeline' that integrates advanced AI reasoning directly into the SDLC. It acts as an intelligent gatekeeper, automating high-stakes audits across three domains: identifying memory vulnerabilities in Linux Kernel patches, detecting massive cost drifts in Terraform plans, and translating natural language security intent into hardened Kubernetes manifests.

A systematic protocol for repairing broken features by scoping the module, tracing every dependency, diagnosing issues, fixing them, and verifying results—ideal when a feature needs end-to-end debugging rather than a quick patch.

This agent facilitates comprehensive debugging and testing of iOS applications running on a simulated environment. It leverages XcodeBuildMCP to manage the entire lifecycle, including building, running, interacting with the UI (tap, type, gesture), taking screenshots, and capturing detailed runtime logs. Use it whenever you need to simulate real-world app testing or diagnose issues on a booted simulator.

A comprehensive architectural guide for building and maintaining macOS menubar utilities using SwiftUI and Tuist. It enforces strict separation of concerns by guiding developers to keep networking, state management, and UI presentation in distinct, testable layers, ensuring robust and scalable application development.

This skill acts as an anti-over-engineering guardrail, instructing AI coding agents to maintain strict scope control and minimalism. It guides the AI to only modify the files and lines explicitly requested by the user, avoiding unnecessary abstractions, unrequested refactors, or scope creep. Use it when you prefer the simplest, most direct solution and want to prevent the agent from 'grinding' the code base.

This skill systematically audits a given project by analyzing its historical memory, rollout summaries, and local skill definitions. It identifies repeated complex workflows, recurring operational patterns, or areas where existing skills are stale. The audit process guides the user to recommend the highest-value skills to either add (if a new pattern emerges) or update (if current skills are outdated or incomplete), ensuring the AI agent operates with the most accurate and context-specific knowledge base for optimal project execution.

A comprehensive guide to diagnosing and resolving performance bottlenecks in React applications. This skill teaches advanced techniques like state isolation, memoization (using `useMemo`, `useCallback`, and `React.memo`), and list virtualization. It guides users through profiling using React DevTools to identify render hotspots, ensuring components render efficiently and maintain high application responsiveness.

This expert reviews and rectifies complex Swift Concurrency issues, such as actor isolation violations, Sendable safety breaches, and data races. It applies modern patterns (like `@MainActor` and `actor` usage) to ensure code adheres to Swift 6.2+ standards while minimizing behavior changes. Use it when debugging concurrency warnings or migrating legacy codebases.

A comprehensive guide for building or reviewing SwiftUI User Interfaces that utilize the modern Liquid Glass aesthetic. This skill focuses on correctly implementing native Apple APIs (like `glassEffect` and `GlassEffectContainer`) while ensuring proper fallback mechanisms, modifier ordering, and performance for iOS 26+ devices. Ideal for adopting cutting-edge iOS design patterns.

This skill provides a comprehensive, structured workflow for diagnosing performance bottlenecks in SwiftUI applications. It guides users through a code-first review to detect common issues like invalidation storms, layout thrash, or heavy main-thread work. When code review is insufficient, it provides detailed guidance on collecting runtime evidence using Instruments, enabling precise root cause analysis and targeted remediation strategies.